Evolution of system connectivity to support food production in the Indus Basin in Pakistan.

Sustainability challenges related to food production arise from multiple nature-society interactions occurring over long time periods. Traditional methods of quantitative analysis do not represent long-term changes in the networks of system components, including institutions and knowledge that affect system behavior. Here, we develop an approach to study system structure and evolution by combining a qualitative framework that represents sustainability-relevant human, technological, and environmental components, and their interactions, mediated by knowledge and institutions, with network modeling that enables quantitative metrics. We use this approach to examine the water and food system in the Punjab province of the Indus River Basin in Pakistan, exploring how food production has been sustained, despite high population growth, periodic floods, and frequent political and economic disruptions. Using network models of five periods spanning 75 y (1947 to 2022), we examine how quantitative metrics of network structure relate to observed sustainability-relevant outcomes and how potential interventions in the system affect these quantitative metrics. We find that the persistent centrality of some and evolving centrality of other key nodes, coupled with the increasing number and length of pathways connecting them, are associated with sustaining food production in the system over time. Our assessment of potential interventions shows that regulating groundwater pumping and phasing out fossil fuels alters network pathways, and helps identify potential vulnerabilities for future food production.

Equity and modeling in sustainability science: Examples and opportunities throughout the process.

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

Multi-objective optimization of energy and greenhouse gas emissions in water pumping and treatment.

A large part of operating costs in urban water supply networks is usually due to energy use, mostly in the form of electricity consumption. There is growing pressure to reduce energy use to help save operational costs and reduce carbon emissions. However, in practice, reducing these costs has proved to be challenging because of the complexity of the systems. Indeed, many water utilities have concluded that they cannot practically achieve further energy savings in the operation of their water supply systems. This study shows how a hybrid linear and multi-objective optimization approach can be used to identify key energy consumption elements in a water supply system, and then evaluate the amount of investment needed to achieve significant operational gains at those points in the supply network. In application to the water supply system for the city of London, the method has shown that up to 18% savings in daily energy consumption are achievable. The optimal results are sensitive to discount rate and the financial value placed on greenhouse gas emissions. Valuation of greenhouse gas emissions is necessary to incentivise high levels of energy efficiency. The methodology can be used to inform planning and investment decisions, with specific focus on reducing energy consumption, for existing urban water supply systems.

A new case for promoting wastewater reuse in Saudi Arabia: bringing energy into the water equation.

Saudi Arabia is the third-largest per capita water user worldwide and has addressed the disparity between its renewable water resources and domestic demand primarily through desalination and the abstraction of non-renewable groundwater. This study evaluates the potential costs of this approach in the industrial and municipal sectors, exploring economic, energy, and environmental costs (including CO2 emissions and possible coastal impacts). Although the energy intensity of desalination is a global concern, it is particularly urgent to rethink water supply options in Saudi Arabia because the entirety of its natural gas production is consumed domestically, primarily in petrochemical and desalination plants. This burgeoning demand is necessitating the development of more expensive high-sulfur gas resources that could make desalination even pricier. The evolving necessity to conserve non-renewable water and energy resources and mitigate GHG emissions in the region also requires policy makers to weigh in much more considerably the energy and environmental costs of desalination. This paper suggests that in Saudi Arabia, the implementation of increased water conservation and reuse across the oil and natural gas sectors could conserve up to 29% of total industrial water withdrawals at costs recovered over 0-30 years, depending on the specific improvement. This work also indicates that increasing wastewater treatment and reuse in six high-altitude inland cities could save a further $225 million (2009 dollars) and conserve 2% of Saudi Arabia's annual electricity consumption. By these estimates, some anticipated investments in desalination projects could be deferred by improving water efficiency in industry and prioritizing investment in sewage and water distribution networks that would ensure more effective water reclamation and reuse. Simultaneously, such initiatives would conserve non-renewable natural gas resources and could help prevent the lock-in of potentially unnecessary desalination infrastructure that is likely to become more energy and cost efficient in future.

Scientific Wealth in Middle East and North Africa: Productivity, Indigeneity, and Specialty in 1981-2013.

Several developing countries seek to build knowledge-based economies by attempting to expand scientific research capabilities. Characterizing the state and direction of progress in this arena is challenging but important. Here, we employ three metrics: a classical metric of productivity (publications per person), an adapted metric which we denote as Revealed Scientific Advantage (developed from work used to compare publications in scientific fields among countries) to characterize disciplinary specialty, and a new metric, scientific indigeneity (defined as the ratio of publications with domestic corresponding authors) to characterize the locus of scientific activity that also serves as a partial proxy for local absorptive capacity. These metrics-using population and publications data that are available for most countries-allow the characterization of some key features of national scientific enterprise. The trends in productivity and indigeneity when compared across other countries and regions can serve as indicators of strength or fragility in the national research ecosystems, and the trends in specialty can allow regional policy makers to assess the extent to which the areas of focus of research align (or not align) with regional priorities. We apply the metrics to study the Middle East and North Africa (MENA)-a region where science and technology capacity will play a key role in national economic diversification. We analyze 9.8 million publication records between 1981-2013 in 17 countries of MENA from Morocco to Iraq and compare it to selected countries throughout the world. The results show that international collaborators increasingly drove the scientific activity in MENA. The median indigeneity reached 52% in 2013 (indicating that almost half of the corresponding authors were located in foreign countries). Additionally, the regional disciplinary focus in chemical and petroleum engineering is waning with modest growth in the life sciences. We find repeated patterns of stagnation and contraction of scientific activity for several MENA countries contributing to a widening productivity gap on an international comparative yardstick. The results prompt questions about the strength of the developing scientific enterprise and highlight the need for consistent long-term policy for effectively addressing regional challenges with domestic research.